In this work we propose a matrix-variate spatiotemporal model to fit two or more response variables, measured at different points in time and distinct locations in space. Here we relax the hypothesis of isotropy in space, since this assumption is not reasonable in various real situations. We treat the anisotropy of the spatial process using the concept of spatial deformation, in a Bayesian framework. Through simulation and also with an illustrative example, we show that the incorporation of spatial deformation into the model can make the interpolation more assertive for some anisotropic scenarios.